Love Wave Group Velocity Tomography of India, Himalaya and Tibet

2020 ◽  
Author(s):  
Monumoy Ghosh ◽  
Supriyo Mitra
Keyword(s):  
Group Velocity ◽  
High Velocity ◽  
Love Wave ◽  
Velocity Structure ◽  
Wave Group ◽  
Low Velocity ◽  
Waveform Data ◽  
Density Map ◽  
Velocity Tomography ◽  
Checker Board

<p>We present Love wave group velocity tomography calculated from broadband waveform data from Indian seismograph networks and global dataset downloaded from the IRIS-DMC. We first calculate path average 1-D fundamental mode Love wave group velocity between 10 s and 120 s period of the Transverse component of the seismograms. Then we combine these 1-D path average measurements using linear tomographic inversion, assuming great circular arc propagation, to compute 2-D group velocity map of the region at discrete periods. The region is adaptively parametrized to get high resolution at higher raypath density. We performed checker-board test to ascertain the resolution of the tomography maps and compute ray density map, raypath cross density map, and raypath orientation map to quantitatively analyze the controls of these parameters on the checker board resolution recovery. Tomographic maps at lower period show good correlation to the local geologic structures like low velocity in basins and high velocity in cratons and shields. At mid-period maps high velocity roots of cratons and low velocity in Tibet and Andaman- Burma subduction can be seen. At higher period low velocity in Tibet conforms with previous observations. We will do linear inversion of Love wave group velocity to get 3D SH wave velocity structure of the region.</p>

scholarly journals Group velocity maps using subspace and Trans-dimensional inversions: ambient noise tomography in the Western part of Java, Indonesia

2019 ◽  
Author(s):  
Shindy Rosalia ◽  
Phil Cummins ◽  
Sri Widiyantoro ◽  
Tedi Yudistira ◽  
Andri Dian Nugraha ◽  
...  
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Ambient Noise ◽  
Regularization Parameter ◽  
Least Square ◽  
Disaster Mitigation ◽  
Wave Group ◽  
Ambient Noise Tomography ◽  
Waveform Data ◽  
Subspace Optimization

Summary In this paper, we compare two different methods for group velocity inversion: iterative, least-squares subspace optimization, and probabilistic sampling based on the Trans-dimensional Bayesian method with tree-based wavelet parameterization. The wavelet parameterization used a hierarchical prior for wavelet coefficients which could adapt to the data. We applied these inversion methods for ambient noise tomography of the western part of Java, Indonesia. This area is an area prone to multiple geological hazards due to its proximity to the subduction of the Australia Plate beneath Eurasia. It is therefore important to have a better understanding of upper crustal structure to support seismic hazard and disaster mitigation efforts in this area. We utilized a new waveform dataset collected from 85 temporary seismometers deployed during 2016–2018. Cross-correlation of the waveform data was applied to retrieve empirical Rayleigh wave Green's functions between station pairs, and the spatial distribution of group velocity was obtained by inverting dispersion curves. Our results show that, although computationally expensive, the Trans-dimensional Bayesian approach offered important advantages over optimization, including more effective explorative of the model space and more robust characterization of the spatial pattern of Rayleigh wave group velocity. Meanwhile, the iterative, least-square subspace optimization suffered from the subjectivity of choice for reference velocity model and regularization parameter values. Our Rayleigh wave group velocity results show that for short (1–10 s) periods group velocity correlates well with surface geology, and for longer periods (13–25 s) it correlates with centers of volcanic activity.

Crust-mantle velocity structure in Shanxi rift, Central North China Craton

2020 ◽  
Author(s):  
Yan Cai ◽  
Jianping Wu
Keyword(s):  
Upper Mantle ◽  
High Velocity ◽  
North China Craton ◽  
Lower Crust ◽  
North China ◽  
Velocity Structure ◽  
Low Velocity ◽  
Crust And Upper Mantle ◽  
The North ◽  
Shanxi Rift

<p>North China Craton is the oldest craton in the world. It contains the eastern, central and western part. Shanxi rift and Taihang mountain contribute the central part. With strong tectonic deformation and intense seismic activity, its crust-mantle deformation and deep structure have always been highly concerned. In recent years, China Earthquake Administration has deployed a dense temporary seismic array in North China. With the permanent and temporary stations, we obtained the crust-mantle S-wave velocity structure in the central North China Craton by using the joint inversion of receiver function and surface wave dispersion. The results show that the crustal thickness is thick in the north of the Shanxi rift (42km) and thin in the south (35km). Datong basin, located in the north of the rift, exhibits large-scale low-velocity anomalies in the middle-lower crust and upper mantle; the Taiyuan basin and Linfen basin, located in the central part, have high velocities in the lower crust and upper mantle; the Yuncheng basin, in the southern part, has low velocities in the lower crust and upper mantle velocities, but has a high-velocity layer below 80 km. We speculate that an upwelling channel beneath the west of the Datong basin caused the low velocity anomalies there. In the central part of the Shanxi rift, magmatic bottom intrusion occurred before the tension rifting, so that the heated lithosphere has enough time to cool down to form high velocity. Its current lithosphere with high temperature may indicate the future deformation and damage. There may be a hot lithospheric uplift in the south of the Shanxi rift, heating the crust and the lithospheric mantle. The high-velocity layer in its upper mantle suggests that the bottom of the lithosphere after the intrusion of the magma began to cool down.</p>

Surface‐wave group‐velocity tomography for shallow structures at a waste site

1999 ◽  
Author(s):  
Leland Timothy Long ◽  
Argun Kocaoglu ◽  
William E. Doll ◽  
Xiuqi Chen ◽  
Jeffrey Martin
Keyword(s):  
Surface Wave ◽  
Group Velocity ◽  
Wave Group ◽  
Waste Site ◽  
Velocity Tomography

Rayleigh- and Love-wave dispersion up to 140-second-period range in the Indonesia-Philippine region

1975 ◽  
Vol 65 (2) ◽  
pp. 507-521
Author(s):  
Harsh K. Gupta ◽  
Kazuo Hamada
Keyword(s):  
Rayleigh Wave ◽  
Group Velocity ◽  
Love Wave ◽  
Active Regions ◽  
Wave Dispersion ◽  
Wave Group ◽  
Period Range ◽  
Moving Window Analysis ◽  
Love Wave Dispersion ◽  
Group Velocities

abstract Group velocities for Rayleigh waves extending to 140-sec-period range have been determined for 10 paths in the Indonesia-Philippine region using moving window analysis. The group velocities for five of these paths have been determined from the vertical as well as the longitudinal components and the values obtained from the two components tally with each other. It has also been possible to obtain Love-wave group velocities for three of these paths. On the basis of group-velocity values and regions covered, the observed Rayleigh-wave group-velocity data could be divided into three groups. The first group includes data for paths mostly confined to deep ocean and the observed data could be explained by standard oceanic models such as 8099. The second group includes data for paths lying partially within seismically active regions and models ARC-1 and ALRDG-9 fit with these data. The third group shows still lower group velocities for paths entirely confined to seismically active regions. The shear velocities inferred from Love-wave dispersion data are higher than those inferred from Rayleigh-wave data. In general, the group velocities varied greatly within small distances even in the longer period range, indicating strong lateral heterogeneities in the mantle.

scholarly journals A MATLAB Package for Calculating Partial Derivatives of Surface-Wave Dispersion Curves by a Reduced Delta Matrix Method

2019 ◽  
Vol 9 (23) ◽  
pp. 5214 ◽  
Author(s):  
Wu ◽  
Wang ◽  
Su ◽  
Zhang
Keyword(s):  
Surface Wave ◽  
Group Velocity ◽  
Love Wave ◽  
Wave Dispersion ◽  
Dispersion Curves ◽  
Wave Group ◽  
Surface Wave Dispersion ◽  
Partial Derivatives ◽  
Matlab Package ◽  
Derivatives Of

Various surface-wave exploration methods have become increasingly important tools in investigating the properties of subsurface structures. Inversion of the experimental dispersion curves is generally an indispensable component of these methods. Accurate and reliable calculation of partial derivatives of surface-wave dispersion curves with respect to parameters of subsurface layers is critical to the success of these approaches if the linearized inversion strategies are adopted. Here we present an open-source MATLAB package, named SWPD (Surface Wave Partial Derivative), for modeling surface-wave (both Rayleigh- and Love-wave) dispersion curves (both phase and group velocity) and particularly for computing their partial derivatives with high precision. The package is able to compute partial derivatives of phase velocity and of Love-wave group velocity analytically based on the combined use of the reduced delta matrix theory and the implicit function theorem. For partial derivatives of Rayleigh-wave group velocity, a hemi-analytical method is presented, which analytically calculates all the first-order partial differentiations and approximates the mixed second-order partial differentiation term with a central difference scheme. We provide examples to demonstrate the effectiveness of this package, and demo scripts are also provided for users to reproduce all results of this paper and thus to become familiar with the package as quickly as possible.

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